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DTSTAMP:20250626T234542Z
LOCATION:B309
DTSTART;TZID=America/New_York:20241117T163000
DTEND;TZID=America/New_York:20241117T163500
UID:submissions.supercomputing.org_SC24_sess736_ws_pdswwip113@linklings.co
 m
SUMMARY:When Stream Processing Engine Meets Log-Structured Merge-Tree as S
 tate Store
DESCRIPTION:Kyuli Park and Sungyong Park (Sogang University, South Korea)\
 n\nIn the era of big data, where vast amounts of real-time data are genera
 ted, stream processing engines (SPEs) are widely utilized across various i
 ndustries. In particular, SPEs that process stateful queries utilize histo
 rical data to execute current queries. We address the problem that occurs 
 when a Log Structured Merge Tree-based Kev-Value Store (LSM-KVS) meets an 
 SPE as a state store. We found that LSM operations that occur synchronousl
 y within an SPE affect the SPE, and additionally introduce the I/O operati
 ons that occur as a result of LSM operations.\n\nTag: Data Movement and Me
 mory, I/O, Storage, Archive\n\nRegistration Category: Workshop Reg Pass\n\
 nSession Chairs: Suren Byna (The Ohio State University, Lawrence Berkeley 
 National Laboratory (LBNL)); Dean Hildebrand (Google LLC); Anthony Kougkas
  (Illinois Institute of Technology, Argonne National Laboratory (ANL)); Ja
 y Lofstead (Sandia National Laboratories, University of New Mexico); and B
 ing Xie (Microsoft Corporation)\n\n
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